Meng et al. BMC Medical Genetics 2020, 21(Suppl 1):176
https://doi.org/10.1186/s12881-020-01099-7

RESEARCH

Open Access

Understanding the molecular association
between hyperkalemia and lung squamouscell carcinomas
Xianping Meng1†, Hongyan Lu2†, Xia Jiang2, Bin Huang2, Song Wu2, Guiping Yu2*

and Hongbao Cao3,4*

From 11th International Young Scientists School “Systems Biology and Bioinformatics” – SBB-2019
Novosibirsk, Russia. 24-28 June 2019

Abstract
Background: Previous studies indicated a strong association between hyperkalemia and lung squamous cell
carcinomas (LSCC). However, the underlying mechanism is not fully understood so far.
Methods: Literature-based data mining was conducted to identify genes, molecule, and cell processes linked toboth hyperkalemia and LSCC. Pathway analysis was performed to explore the interactive network, common-target
network, and common-regulator network for both disorders. Then, a mega-analysis using 11 independent LSCC
RNA expression datasets (358 LSCCs and 278 healthy controls) was performed to test the hypothesis that genes
influencing hyperkalemia may also play roles in LSCC.
Results: There was a significant overlap between the genes implicated with both diseases (20 genes, p-value = 4.98e15), which counts for 16% of all hyperkalemia genes (125 genes). Network analysis identified 12 molecules as common
targets for hyperkalemia and LSCC, and 19 molecules as common regulators. Moreover, 19 molecules were identified
within an interactive network, through which hyperkalemia and LSCC could exert influence on each other. In addition,
meta-analysis identified one hyperkalemia promoter, SPP1, as a novel contributor for LSCC (LFC = 2.64; p-value = 2.81e6). MLR analysis suggests geographical region as an influential factor for the expression levels of SPP1 in LSCC patients(p value = 0.036, 0.054).
Conclusion: Our results showed that there was a common molecular basis for the pathology of both hyperkalemiaand LSCC, and that genes promoting hyperkalemia might also play roles in the development of LSCC. However, thisstudy did not suggest hypercalcemia as a casual factor for LSCC.
Keywords: Hyperkalemia, Lung squamous cell carcinomas, Mega-analysis, Pathway analysis, Multiple linear regression
analysis* Correspondence: g.yu@gousinfo.com; caohon2010@gmail.com†
Xiangping Meng and Hongyan Lu contributed equally to this work.
2
Department of Cardiothoracic Surgery, The affiliated Jiangyin Hospital ofSoutheast University Medical College, Jiangyin 214400, Jiangsu, China
3
Department of Psychiatry, First Hospital/First Clinical Medical College of
Shanxi Medical University, Taiyuan 030001, Shanxi Province, China
Full list of author information is available at the end of the article© The Author(s). 2020 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License,
which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give
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Meng et al. BMC Medical Genetics 2020, 21(Suppl 1):176

Background
Hyperkalemia is an elevated level of potassium (K+)
in the blood (> 5.5 mmol/L), which is caused by abnormalities in the normal bone formation and degradation cycle, and leading to increased calcium (Ca2+)level in the blood serum [1]. About 30% of cancer patients demonstrate hyperkalemia [1, 2], especially insquamous cell carcinomas of head and neck, esophageal, cervical, and lung [2].
A strong association was reported between hyperkalemia and lung squamous cell carcinomas (LSCC) [3]. It isaffecting patients in progressive stages, shortening survival times, and leading to poor prognosis [3]. Genetic
mutations have also been reported to support the relationship between both diseases. Nielsen et al. found that
ectopic PTH-producing squamous cell lung carcinoma
associated with humoral hyperkalemia of malignancy [4].
Lorch et al. reported that EGFR-induced Ras-mitogenactivated protein kinase signaling accounts for highlevels of PTHrP expression, and contributes to humoral
hypercalcaemia of malignancy caused by LSCC [5].
These observations indicate the presence of some notyet-discovered connections between both diseases besides the existing genetic relations.
To understand the molecular association between
hyperkalemia and LSCC, we performed a large scaledisease-gene relation data analysis and pathways analysis
to explore potential pathways and networks that influencing both disorders. Then a mega-analysis was conducted to test the hypothesis that genes increase theiractivities with hyperkalemia may also play a role in thedevelopment of LSCC. Our study provides new insights
into the understanding of the hyperkalemia-LSCC association and suggests a novel approach to examine influential genes for LSCC.
Methods

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association of a candidate gene with hyperkalemia
and/or LSCC.
Functional pathway analysis

After the hyperkalemia and LSCC relation data being
curated, a literature-based functional pathway analysis
was conducted with an aim to identify pathways/networks that linking both disorders. Moreover, after
mega-analysis, pathway analysis was used to identify
the potential biological linkage between LSCC andnovel target genes from mega-analysis results. The
pathway analysis was performed using the ‘Shortest
Path’ module of Pathway Studio (www.pathwaystudio.
com). A follow-up mega-analysis was used to validate
the activity of the genes within the functional
pathway.
LSCC RNA expression datasets selection for mega-analysis

A keyword ‘lung squamous cell carcinomas’ was used tosearch LSCC expression datasets at the website of GEO(https://www.ncbi.nlm.nih.gov/geo/). Then, the datasets
were further filtered by the following criteria: 1) The
entry type is series; 2) The study type is RNA expression;3) The sample size is no less than 10; 4) Sample organism is Homo sapiens; and 4) the studies were performed
according to a case vs. normal control design.
To note, the selection of the data covers all LSCC expression array datasets from GEO, which is owned by
the National Institutes of Health (NIH of USA). The
datasets are publicly available, and no permission orconfirmation is needed from any independent investigators. Moreover, datasets extraction has no selection bias
in terms of publication journals, owner affiliations, andauthors. In addition, the original data rather than theprocessed results of each dataset were used to performthe analysis in this study, which avoids possible noisecaused by the independent data process.

Large-scale literature data mining

Relation data for both hyperkalemia and LSCC wereextracted from existing literature and analyzed using
Pathway Studio (www.pathwaystudio.com) and thenwere downloaded into a genetic database Hyperkalemia_LSCC, hosted at http://database.gousinfo.com.
The downloadable format of the database in excel isavailable at http://gousinfo.com/database/Data_Genetic/Hyperkalemia_LSCC.xlsx. Besides the list of analyzed genes (Hyperkalemia_LSCC→Hyperkalemia_
genes, LSCC_genes, and Hyperkalemia_specific genes),
supporting references for each disease-gene relation
are presented at Hyperkalemia_LSCC→Hyperkalemia_
gene_relation and LSCC_gene_relation, including titlesof the references and the sentences describing identified disease-gene relationships. The information could
be used to locate a detailed description of an

Mega-analysis models

To estimate the effect size of hyperkalemia related
genes in the case of LSCC, we applied two models
for the mega-analysis, including the fixed-effect modeland random-effects model [6]. Results from bothmodels were reported and compared. During the processing of the datasets, all the expression data werenormalized and log2-transformed if not done in theoriginal dataset.
The heterogeneity of the mega-analysis was analyzed
to study the variance within and between different studies. In the case that the total variance Q is equal to or
smaller than the expected between-study variance df, theeq. (1) will be set as 0, and a fixed-effect model was selected for the mega-analysis. Otherwise, a randomeffects model was selected.

Meng et al. BMC Medical Genetics 2020, 21(Suppl 1):176

ISq ¼

Q − df
100%
Q

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ð1ÞFor each gene within an LSCC-expression dataset, thelog fold change (LFC) was calculated and used as theindex of effect size in mega-analysis. The Q-p represents
the probability that the total variance is coming fromwithin-study only. All analysis was conducted by anindependently-developed MATLAB (R2017a) megaanalysis package.
The significant genes identified and selected frommega-analysis must be qualified by the following criteria:p < 0.005 and effect size abs (LFC) > 1. The details of themega-analysis results were presented in the Hyperkalemia_LSCC→Mega-analysis.
Multiple linear regression analysis for the risk factors on
LSCC

A multiple linear regression analysis was utilized to
study the possible influence of three factors on the gene
expression change in LSCC: sample size, population region, and study age. P-values and 95% confidence interval (CI) were reported for each of the factors. The
analysis was done in Matlab (R 2017a) with the ‘regress’
statistical analysis package.

value = 4.98e-15), with 105 out of the 125 hyperkalemiarelated genes have not been implicated in LSCC (seeFig. 1).
Common targets and regulators of hyperkalemia and
LSCC

Pathway analysis identified a common-target network(Fig. 2a) and a common-regulator network (Fig. 2b). On
the one hand, we see that hyperkalemia and LSCC both
regulating the activity of 11 proteins and one molecule(Ca2+). On the other hand, we identified 11 small molecules, 4 genes and 2 cell types as common regulators forboth LSCC and hyperkalemia. These networks indicatethat LSCC and hyperkalemia share a deep molecularbasis in their pathological development.
An interactive network connecting hyperkalemia and
LSCC

Besides the common targets and common regulators, we
also discovered an interactive network that connecting
hyperkalemia and LSCC, as shown in Fig. 3. Interestingly, we see that not only LSCC could be a causal factor
for hyperkalemia by regulating multiple molecules (Fig.
3, the molecules highlighted in green), but hyperkalemia
also contributes to the development of LSCC throughthe influence on multiple genes (Fig. 3, the genes
highlighted in red).

Results
Disease-related genes from the literature database

Mega-analysis results

We acquired both diseases related genes by using the
Pathway Studio guided literature data-mining (www.
pathwaystudio.com), yielding 125 Hyperkalemia-genes
and 397 LSCC-genes (see Hyperkalemia_LSCC: hyperkalemia_genes and LSCC_genes). There was a significant
overlap between the two gene groups (20 genes; p-

As shown in Table 1, a total of 11 independent RNA expression datasets qualified the filter criteria were utilized
for the mega-analysis. The expression data acquired
from 358 LSCC cases and 278 healthy controls were distributed in seven different countries with the study age
ranged from 2 to 13 years.

Fig. 1 Venn diagram of the genes implicated with hyperkalemia and lung squamous cell carcinoma

Meng et al. BMC Medical Genetics 2020, 21(Suppl 1):176

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Fig. 2 Common regulators and targets of hyperkalemia and lung squamous cell carcinoma. a Common targets; b Common regulators

During the study, a log fold change (LFC) was estimatedfor each of the 105 hyperkalemia-specific genes from the
majority of the 11 studies. Results showed that one gene,
SPP1, presented significant increased LFC in the case of
LSCC (p = 2.81e-6 and LFC = 2.64). Notably, SPP1 was implicated as a hyperkalemia promoter. Heterogeneity analysis results showed that there was a significant betweenstudy variance for mega-analysis (p-value = 2.81e-6), andtherefore a random-effects model was selected. The related statistics were presented in Table 2.
Figure 4a presents the forest-plot from the megaanalysis for SPP1, including LFC, weight, and 95% confidence interval (CI). Figure 4b demonstrates the potential
pathways through which SPP1 may contribute to thepathologic development of LSCC. To note, the pathway

in Fig. 4b was firstly built through literature-based pathway analysis, then we conducted another mega-analysis
to test the activity of these molecules in case of LSCC,
using the 11 LSCC RNA expression datasets listed inTable 1. Results show that SPP1 activates the expressionof multiple LSCC promoters, including PTK2, MMP1,
SDC1, and FOXM1, both directly and through the activation of PLAU (Fig. 4b).

MLR analysis results

Results from the MLR models showed that the population region (country) demonstrated significance for
influencing the expression levels of SPP1 (p-value =0.054 and 0.036, respectively), as shown in Table 2.

Fig. 3 Interactive network through which hyperkalemia and lung squamous cell carcinoma may influence each otherMeng et al. BMC Medical Genetics 2020, 21(Suppl 1):176

Page 5 of 7

Table 1 Datasets selection for mega-analysis
Study Name

Dataset GEOID

nControlnCase

Country

Nazarov et al.,2017

GSE84784

99Luxembourg

Study Age
2

Tong et al.,2016

GSE67061

8

69

China

3

Rousseaux et al.,2014

GSE30219

14

61

France5

Mascaux et al.,2014

GSE33479

27

14

USA

5

Girard et al.,2012

GSE32036

59

12

USA

7

Philipsen et al.,2010

GSE19188

65

27

Netherlands

9

Takahashi et al.,2009

GSE11969

5

35

Japan

10

Boelens et al.,2009

GSE12472

28

35

Netherlands

10

Ishikawa et al.,2009

GSE2088

30

48

Japan

10

Boelens et al.,2008

GSE12428

28

34

Netherlands

11

Rosskopf et al.,2006

GSE6044

5

14

Germany

13

The sample size and study age were not significant
risk factors.

Discussion
Previous studies suggested the causal effects of cancers
for hyperkalemia [2], as well as the negative influence ofhyperkalemia on the prognosis of LSCC [3]. The purpose of our study is to explore the potential molecularmechanisms underlying the clinical association between
hyperkalemia and LSCC. Based on the discovery, we
made one further step to test the hypothesis that genes
promoting hyperkalemia may also play roles in the development of LSCC.
Assisted by using the tool Pathway Studio (www.
pathwaystudio.com), we conducted a large-scale literature data mining, covering over 40 million references to
identify LSCC and hyperkalemia related genes, proteins,
small molecules, and cell types. Based on the mining results, pathway analysis has been conducted to identify
common targets and common regulators of LSCC andhyperkalemia. We also discovered a potential crossnetwork through which LSCC and hyperkalemia may
Table 2 SPP1 mega-analysis and regression analysis results
Gene Name

SPP1

Random-Effects Model
Datasets included

11

LFC

2.64

STD of LFC

0.58

p-value

2.81e-6

ISQ

45.86

p-value-Q

0.048

Multiple linear regression analysis
Sample Size

0.64

Population Region

0.054

Study Age

0.62

connect with each other and mutually impact theirpathologic development.
On the one hand, previous studies showed that LSCC
and hyperkalemia influenced by multiple common molecules. For instance, macrophages play a vital role in thedevelopment of LSCC and hyperkalemia [7, 8]. Moreover, squamous carcinoma cell lines experiments showedthat abnormal TP53 expression could cause hyperkalemia [9], while the mutation of TP53 has been suggested
to play roles in the development of LSCC [10]. On theother hand, LSCC and hyperkalemia have an influenceon multiple common molecules. It has been shown that
increased calcium content is an indicator of LSCC [11],while hyperkalemia stimulates enzyme secretion and elevates calcium concentration [12]. It has also been suggested that the amplification and overexpression of
MYC have been reported previously in both LSCC andhyperkalemia type carcinoma [13].
In addition, multiple evidence from previous studies
indicated that hyperkalemia and LSCC could be mutual
causal factors for each other. As shown in Fig. 3, besides
the promotion of calcium [11], LSCC also activates multiple genes that produce hyperkalemia, including EGFR,
EZH2 [5, 14]. These studies partially explain the mechanism that LSCC induces hyperkalemia. On the other
hand, hyperkalemia has been shown to stimulate the expression of multiple genes or proteins that promote thedevelopment of LSCC. For instance, hyperkalemia patients demonstrated elevated ACE levels [15], which leadto an increased risk of LSCC [16]. Hyperkalemia also
stimulates the expression of PTGS2 [17], which plays animportant role in the rat LSCC [18] and has been suggested as a therapeutic target for LSCC [19]. These studies indicated that hyperkalemia might be a risk factor
that promotes the development of LSCC.
Based on the association study between LSCC andhyperkalemia, it is reasonable to hypothesize that genes
promoting hyperkalemia may also play roles in the

Meng et al. BMC Medical Genetics 2020, 21(Suppl 1):176

Page 6 of 7

Fig. 4 SPP1 presented significant effects in case of LSCC

development of LSCC. Venn diagrams in Fig. 1 showedthat 16% (20/125) genes implicated with hyperkalemia
have also been suggested an association with LSCC.
Fisher exact test showed that the probability that two
random gene groups with the same size of genes (i.g.,
125 and 397 genes) to have an overlap of 20 is less than
4.98e-15, which supports the hypothesis proposed here.
In addition, mega-analysis discovered one hyperkalemiaspecific promoter, SPP1, also presented significantly increased expression in the case of LSCC (p = 2.81e-6; LFC =2.64) (Table 2, Fig. 4b). MLR analysis results suggested thatthe population region (country) was a factor that affects theexpression level of SPP1 in the case of LSCC (P-value =0.054). Pathway analysis showed that SPP1 might promote
the pathological development of LSCC through the stimulation of the expression of multiple genes, as shown in Fig. 4b.
Overexpression of SPP1 was reported to be associated withpoor prognosis, progression, migration, and invasion of multiple cancers [20–23]. The elevated expression of SPP1 could
result in the up-regulation of SDC1 signaling (gene coloredin red, Fig. 2), which promotes the metastasis in LSCC [24].
Moreover, SPP1 induces increased PLAU production that indirectly activates MMP1, which promotes tumor progression
and LSCC cell migration and invasion [25, 26]. The pathway
presented in Fig. 4b provides further support for the hypothesis that genes promoting hyperkalemia may also play rolesin the development of LSCC. To note, the activities of thegenes within the SPP1 signaling pathway (Fig. 4b) have beenvalidated by the mega-analysis using the 11 independent
datasets listed in Table 1.

To note, this study was designed to explore the mechanism of LSCC-hyperkalemia mechanism at the molecular level. The shared genetic pathways and moleculartargets and regulators may partially explain the mutual
influence of LSCC and hyperkalemia. However, our results did not suggest a causal effect of hyperkalemia on
LSCC.

Conclusion
Our results suggested that LSCC and hyperkalemia havea shared pathological basis and are mutual influential
factors for each other. Genes associated with hyperkalemia may also play roles for the development of LSCC,
and SPP1 could be a promoter for both hyperkalemiaand LSCC.
Abbreviations
LSCC: Lung squamous cell carcinomas; LFC: Log fold change; CI: Confidence
interval
Acknowledgements
Not applicable.
About this supplement
This article has been published as part of BMC Medical Genetics Volume 21
Supplement 1, 2020: Selected Topics in “Systems Biology and Bioinformatics”- 2019: medical genetics. The full contents of the supplement are available
online at https://bmcmedgenet.biomedcentral.com/articles/supplements/
volume-21-supplement-1.
Authors’ contributions
XM, GY and HC developed the study design. HC, HL, XJ, SW and BH
contributed to the data collection, analysis and paper writing; XM, and GY
partially contributed to data analysis and paper writing; HC, XM, HL, XJ andMeng et al. BMC Medical Genetics 2020, 21(Suppl 1):176

GY contributed to the revise of the manuscript; The authors read andapproved the final manuscript.
Funding
The authors received no funding for this study; Corresponding author willtake the responsibility for the publication fee.
Availability of data and materials
All data supporting the findings of this study are available from thecorresponding author in response to a reasonable request.
Ethics approval and consent to participate
Not applicable.
Consent for publication
Not applicable.
Competing interests
The authors declare no conflict of interest.
Author details
1
Department of Radiology, Jiangyin People’s Hospital, Jiangyin 214400,
Jiangsu Province, China. 2Department of Cardiothoracic Surgery, Theaffiliated Jiangyin Hospital of Southeast University Medical College, Jiangyin
214400, Jiangsu, China. 3Department of Psychiatry, First Hospital/First Clinical
Medical College of Shanxi Medical University, Taiyuan 030001, Shanxi
Province, China. 4Department of Genomics Research, RD Solutions, Elsevier
Inc, Rockville, MD 20852, USA.
Published: 22 October 2020
References
1. Minisola S, Pepe J, Piemonte S, Cipriani C. The diagnosis and managementof hypercalcaemia. BMJ. 2015;350:h2723.
2. Stewart AF. Clinical practice. Hyperkalemia associated with cancer. N Engl J
Med. 2005;352(4):373–9.
3. Li X, Bie Z, Zhang Z, Li Y, Hu X, Liu W, et al. Clinical analysis of 64 patientswith lung-cancer-associated hyperkalemia. J Cancer Res Ther. 2015;
11(Suppl):C275–9.
4. Nielsen PK, Rasmussen AK, Feldt-Rasmussen U, Brandt M, Christensen L,
Olgaard K. Ectopic production of intact parathyroid hormone by asquamous cell lung carcinoma in vivo and in vitro. J Clin Endocrinol Metab.
1996;81(10):3793–6.
5. Lorch G, Gilmore JL, Koltz PF, Gonterman RM, Laughner R, Lewis DA, et al.
Inhibition of epidermal growth factor receptor signalling reduces
hypercalcaemia induced by human lung squamous-cell carcinoma inathymic mice. Br J Cancer. 2007;97(2):183–93.
6. Borenstein M, Hedges LV, Higgins JP, Rothstein HR. A basic introduction to
fixed-effect and random-effects models for mega-analysis. Res Synth
Methods. 2010;1(2):97–111.
7. Dai YB, Miao YF, Wu WF, Li Y, D'Errico F, Su W, et al. Ablation of liver X
receptors α and β leads to spontaneous peripheral squamous cell lungcancer in mice. Proc Natl Acad Sci U S A. 2016;113(27):7614–9.
8. Fogo AB, Lusco MA, Najafian B, Alpers CE. AJKD atlas of renal pathology:
sarcoidosis. Am J Kidney Dis. 2016;68(1):e5–6.
9. Foley J, King CS, Jiménez JA, Wysolmerski JJ, Philbrick WM. Activation of
PTHrP gene expression in squamous carcinoma cell lines by mutant
isoforms of the tumor suppressor p53. Oncol Res. 2000;12(2):71–81.
10. Wang YC, Lee HS, Chen SK, Chang YY, Chen CY. Prognostic significance of
p53 codon 72 polymorphism in lung carcinomas. Eur J Cancer. 1999;35(2):226–30.
11. Wu F, Zhou H, Li F, Wang JT, Ai T. Spectral CT imaging of lung Cancer:
quantitative analysis of spectral parameters and their correlation with tumor
characteristics. Acad Radiol. 2018;25(11):1398–404.
12. Goebell H, Hotz J. Calcium, pancreatic secretion and pancreatitis (author'stransl). Leber Magen Darm. 1976;6(4):211–6.
13. Tandon B, Hagemann IS, Maluf HM, Pfeifer JD, Al-Kateb H. Association of LiFraumeni Syndrome with Small Cell Carcinoma of the ovary, hypercalcemic
type and concurrent pleomorphic Liposarcoma of the cervix. Int J Gynecol
Pathol. 2017;36(6):593–9.

Page 7 of 7

14. Wang Y, Chen SY, Karnezis AN, Colborne S, Santos ND, Lang JD, et al. The
histone methyltransferase EZH2 is a therapeutic target in small cell
carcinoma of the ovary, hypercalcaemic type. J Pathol. 2017;242(3):371–83.
15. Tuohy KA, Steinman TI. Hypercalcemia due to excess 1,25-dihydroxyvitamin
D in Crohn's disease. Am J Kidney Dis. 2005;45(1):e3–6.
16. Haznedaroglu IC, Malkan UY. Local bone marrow renin-angiotensin systemin the genesis of leukemia and other malignancies. Eur Rev Med Pharmacol
Sci. 2016;20(19):4089–111.
17. Wang D, An SJ, Wang WH, McGiff JC, Ferreri NR. CaR-mediated COX-2
expression in primary cultured mTAL cells. Am J Physiol Renal Physiol. 2001;
281(4):F658–64.
18. Li HG, Yu LY, Liu MQ, Chen HL, Zhang YX, Liu X, et al. A study on
cyclooxygenase-2 protein expression and vasculature during experimental
rat lung carcinogenesis. Ai Zheng. 2002;21(6):605–9.
19. Kim GY, Lim SJ, Kim YW. Expression of HuR, COX-2, and survivin in lungcancers; cytoplasmic HuR stabilizes cyclooxygenase-2 in squamous cell
carcinomas. Mod Pathol. 2011;24(10):1336–47.
20. Ahmed M, Kundu GC. Osteopontin selectively regulates p70S6K/mTOR
phosphorylation leading to NF-kappaB dependent AP-1-mediated ICAM-1
expression in breast cancer cells. Mol Cancer. 2010;9:101.
21. Delany AM. Matricellular proteins osteopontin and osteonectin/SPARC inpancreatic carcinoma. Cancer Biol Ther. 2010;10(1):65–7.
22. Huang CY, Chang MC, Huang WY, Huang CT, Tang YC, Huang HD, et al.
Urokinase-type plasminogen activator resulting from endometrial
carcinogenesis enhances tumor invasion and correlates with poor outcomeof endometrial carcinoma patients. Sci Rep. 2015;5:10680.
23. Oyama M, Kariya Y, Kariya Y, Matsumoto K, Kanno M, Yamaguchi Y, Hashimoto
Y. Biological role of site-specific O-glycosylation in cell adhesion activity andphosphorylation of osteopontin. Biochem J. 2018;475(9):1583–95.
24. Hu XF, Yao J, Gao SG, Yang YT, Peng XQ, Feng XS. Midkine and syndecan-1
levels correlate with the progression of malignant gastric cardiac
adenocarcinoma. Mol Med Rep. 2014;10(3):1409–15.
25. Rangaswami H, Bulbule A, Kundu GC. Osteopontin: role in cell signaling andcancer progression. Trends Cell Biol. 2006;16(2):79–87.
26. Jessen KA, Liu SY, Tepper CG, Karrim J, McGoldrick ET, Rosner A, et al.
Molecular analysis of metastasis in a polyomavirus middle T mouse model:
the role of osteopontin. Breast Cancer Res. 2004;6(3):R157–69.

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